\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"8499",leadTitle:null,fullTitle:"Differential Diagnosis of Chest Pain",title:"Differential Diagnosis of Chest Pain",subtitle:null,reviewType:"peer-reviewed",abstract:"This book aims to provide an excellent overview of the differential diagnosis and approach to chest pain in various clinical settings. This book is divided into two sections including the introduction and the approach to chest pain. Our introductory chapter starts with the basic principles of statistics and its application in various diagnostic modalities of heart disease. Our authors present a nice approach to patients presenting with chest pain in various scenarios. We have also included a chapter describing GERD, which could present as chest pain and another chapter describing aortic dissection, which is a life-threatening disease presenting with chest pain. We hope that this book will serve as an accessible handbook on the differential diagnosis of chest pain.",isbn:"978-1-83880-590-6",printIsbn:"978-1-83880-589-0",pdfIsbn:"978-1-83880-591-3",doi:"10.5772/intechopen.78875",price:100,priceEur:109,priceUsd:129,slug:"differential-diagnosis-of-chest-pain",numberOfPages:98,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"ac6ad2f79af3af94cb5be97fef057173",bookSignature:"Umashankar Lakshmanadoss",publishedDate:"July 1st 2020",coverURL:"https://cdn.intechopen.com/books/images_new/8499.jpg",numberOfDownloads:4109,numberOfWosCitations:0,numberOfCrossrefCitations:1,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:1,numberOfDimensionsCitationsByBook:2,hasAltmetrics:0,numberOfTotalCitations:2,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 6th 2019",dateEndSecondStepPublish:"September 4th 2019",dateEndThirdStepPublish:"November 3rd 2019",dateEndFourthStepPublish:"January 22nd 2020",dateEndFifthStepPublish:"March 22nd 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"13913",title:"Dr.",name:"Umashankar",middleName:null,surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss",profilePictureURL:"https://mts.intechopen.com/storage/users/13913/images/system/13913.jpg",biography:"Dr. Umashankar Lakshmanadoss completed his training at the University of Rochester, NY, USA. He served as the director of inpatient medical consult service at Johns Hopkins University School of Medicine, Baltimore, MD, USA, and then joined the Division of Cardiovascular Medicine at Guthrie Clinic, Sayre, PA, USA. Then he pursued training in cardiac electrophysiology at William Beaumont School of Medicine and continued advanced cardiac electrophysiology training at Mayo Clinic, Rochester, MN. He served as an assistant professor of medicine in the Division of Cardiology, Louisiana State University, Shreveport, LA, where he also serves as the director of the complex arrhythmia ablation program. His research interest is in the field of cardiac electrophysiology. Currently, he is the director of cardiac electrophysiology at Mercy Health, Cincinnati, OH, USA.",institutionString:"Mercy Health",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"5",institution:{name:"Mercy Health",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"170",title:"Cardiology and Cardiovascular Medicine",slug:"cardiology-and-cardiovascular-medicine"}],chapters:[{id:"71562",title:"Introductory Chapter: The Patient Presenting with Chest Pain",doi:"10.5772/intechopen.91925",slug:"introductory-chapter-the-patient-presenting-with-chest-pain",totalDownloads:629,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"John-Ross D. Clarke",downloadPdfUrl:"/chapter/pdf-download/71562",previewPdfUrl:"/chapter/pdf-preview/71562",authors:[{id:"307190",title:"Dr.",name:"John-Ross",surname:"Clarke",slug:"john-ross-clarke",fullName:"John-Ross Clarke"}],corrections:null},{id:"69344",title:"Application of Bayesian Principles to the Evaluation of Coronary Artery Disease in the Modern Era",doi:"10.5772/intechopen.89440",slug:"application-of-bayesian-principles-to-the-evaluation-of-coronary-artery-disease-in-the-modern-era",totalDownloads:945,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The number of testing modalities available for the diagnosis of significant coronary artery disease has grown over the last few decades. Inappropriate utilization of these tests often leads to: (i) further investigation, (ii) physician and patient uncertainty, (iii) harm and poor outcomes, and (iv) increase in health care costs. An informed approach to the evaluation of the patients with stable ischemic chest pain can lead to efficient use of resources and better outcomes. Throughout the course of this chapter, we will explain how the applications of age-old statistical principles are still relevant in this modern era of technological advancement.",signatures:"John-Ross D. Clarke and Gilead I. Lancaster",downloadPdfUrl:"/chapter/pdf-download/69344",previewPdfUrl:"/chapter/pdf-preview/69344",authors:[{id:"307190",title:"Dr.",name:"John-Ross",surname:"Clarke",slug:"john-ross-clarke",fullName:"John-Ross Clarke"},{id:"307319",title:"Dr.",name:"Gilead",surname:"Lancaster",slug:"gilead-lancaster",fullName:"Gilead Lancaster"}],corrections:null},{id:"69323",title:"Approach to Gastroesophageal Reflux: A Cause of Chest Pain in Infants with Congenital Heart Disease",doi:"10.5772/intechopen.89327",slug:"approach-to-gastroesophageal-reflux-a-cause-of-chest-pain-in-infants-with-congenital-heart-disease",totalDownloads:567,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The life expectancy and quality of life of infants with congenital heart disease have increased in the last 30 years with significant advances in technological facilities, treatment methods, and surgeries. GER is a condition that can be seen in infants with CHD, which needs to be well followed up and to be differentiated between physiological and nonphysiological reflux. GER is a physiological condition that is common in infants with CHD and usually resolves spontaneously in the first 6–12 months of life. If the baby has adequate weight gain and nutrition status and there is no abnormal restlessness, the baby is considered to be uncomplicated GER. GERD is a pathological clinical entity that is accompanied by insufficient weight gain, esophagitis, and persistent respiratory system findings. When gastroesophageal reflux disease is considered, the first thing to be done is to complete the detailed anamnesis and physical examination of the infant. The reflux status of the infants can be examined with the surveys that were prepared for GERD and followed up for 1–2 months. If necessary, diagnostic methods such as esophageal pH monitoring and radiological and endoscopic examinations can be used. Conservative approaches such as thickening of formulas and thickening of formulas and positional feeding are the the first treatment approaches for reflux.",signatures:"Mehmet Semih Demirtaş",downloadPdfUrl:"/chapter/pdf-download/69323",previewPdfUrl:"/chapter/pdf-preview/69323",authors:[{id:"308044",title:"M.D.",name:"Mehmet Semih",surname:"Demirtaş",slug:"mehmet-semih-demirtas",fullName:"Mehmet Semih Demirtaş"}],corrections:null},{id:"72363",title:"Practical Approach to Chest Pain Related to Cardiac Implantable Electronic Device Implantation",doi:"10.5772/intechopen.92743",slug:"practical-approach-to-chest-pain-related-to-cardiac-implantable-electronic-device-implantation",totalDownloads:769,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this review article, we described the common causes and approach for chest pain that happens after cardiac device implantation surgeries. We also describe the clinical features and appropriate treatment for them.",signatures:"Umashankar Lakshmanadoss, Imran Sulemankhil and Karnika Senthilkumar",downloadPdfUrl:"/chapter/pdf-download/72363",previewPdfUrl:"/chapter/pdf-preview/72363",authors:[{id:"13913",title:"Dr.",name:"Umashankar",surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss"},{id:"241871",title:"Ms.",name:"Karnika",surname:"Senthilkumar",slug:"karnika-senthilkumar",fullName:"Karnika Senthilkumar"},{id:"320930",title:"Dr.",name:"Imran",surname:"Sulemankhil",slug:"imran-sulemankhil",fullName:"Imran Sulemankhil"}],corrections:null},{id:"69460",title:"Aortic Dissection",doi:"10.5772/intechopen.89210",slug:"aortic-dissection",totalDownloads:752,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Aortic dissection remains one of the rare but life-threatening causes of chest pain presenting to the emergency department. High index of suspicion is required for prompt diagnosis of the cases presenting to the ED. Symptoms may vary with extent and the progression of the dissection and may further complicate the diagnosis. Thus, patients may present with features of acute MI, CVA, or other end-organ ischemia. Hypertension at presentation may be an important clue for diagnosis of underlying dissection. In low risk patients, D dimer may become a useful screening tool. In patients with high index of suspicion, the choice of investigation will depend on the overall stability of the patient and extent of end-organ ischemia. Stable patients may benefit from CT angiography due to its widespread availability and speed of acquisition. Diagnosis may be challenging for hemodynamically unstable patients in centers where the resources are limited. Transesophageal echocardiography may provide diagnosis in such patients at bedside or in the emergency department. Prompt investigations are required to accurately define the type and extent of damage so that the patient receives life-saving measures in a timely manner.",signatures:"Bina Nasim, Anas Mohammad, Sardar Zafar, Laji Mathew, Ahmed Sajjad, Anis Shaikh and Ghulam Naroo",downloadPdfUrl:"/chapter/pdf-download/69460",previewPdfUrl:"/chapter/pdf-preview/69460",authors:[{id:"68879",title:"Dr.",name:"Ghulam",surname:"Naroo",slug:"ghulam-naroo",fullName:"Ghulam Naroo"},{id:"310650",title:"Dr.",name:"Bina",surname:"Nasim",slug:"bina-nasim",fullName:"Bina Nasim"},{id:"310651",title:"Dr.",name:"Mohammad",surname:"Anas",slug:"mohammad-anas",fullName:"Mohammad Anas"},{id:"310652",title:"Dr.",name:"Sardar",surname:"Zafar",slug:"sardar-zafar",fullName:"Sardar Zafar"},{id:"310653",title:"Dr.",name:"Laji",surname:"Mathew",slug:"laji-mathew",fullName:"Laji Mathew"},{id:"310654",title:"Dr.",name:"Ahmed",surname:"Sajjad",slug:"ahmed-sajjad",fullName:"Ahmed Sajjad"},{id:"310655",title:"Dr.",name:"Anis",surname:"Shaikh",slug:"anis-shaikh",fullName:"Anis Shaikh"}],corrections:null},{id:"71894",title:"Takotsubo Syndrome and Nitric Oxide Bioavailability",doi:"10.5772/intechopen.92235",slug:"takotsubo-syndrome-and-nitric-oxide-bioavailability",totalDownloads:447,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Takotsubo cardiomyopathy, also known as broken heart syndrome or stress cardiomyopathy, is a form of transient left ventricular dysfunction. Severe apical and mid left ventricular hypokinesis with hypercontractility of the basal segments is observed. Numerous underlying causes and pathophysiological mechanisms have been proposed including sudden sympathetic activation and increase in the circulating levels of catecholamines resulting in multivessel coronary spasm. Another possible mechanism related to catecholamine-mediated myocardial stunning is direct myocyte injury. Increasing data show that endothelial dysfunction and depleted nitric oxide bioavailability are common in patients with Takotsubo cardiomyopathy. In this chapter we examine in depth the relation between endothelial dysfunction and Takotsubo syndrome.",signatures:"Michael Demosthenous, Konstantinos Triantafyllou and Nikolaos Koumallos",downloadPdfUrl:"/chapter/pdf-download/71894",previewPdfUrl:"/chapter/pdf-preview/71894",authors:[{id:"44460",title:"Dr.",name:"Nikolaos",surname:"Koumallos",slug:"nikolaos-koumallos",fullName:"Nikolaos Koumallos"},{id:"318818",title:"Dr.",name:"Michael",surname:"Demosthenous",slug:"michael-demosthenous",fullName:"Michael Demosthenous"},{id:"318819",title:"Dr.",name:"Konstantinos",surname:"Triantafyllou",slug:"konstantinos-triantafyllou",fullName:"Konstantinos Triantafyllou"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"965",title:"Novel Strategies in Ischemic Heart Disease",subtitle:null,isOpenForSubmission:!1,hash:"4aacb23e8594bdc279097abdfcde0eb8",slug:"novel-strategies-in-ischemic-heart-disease",bookSignature:"Umashankar Lakshmanadoss",coverURL:"https://cdn.intechopen.com/books/images_new/965.jpg",editedByType:"Edited by",editors:[{id:"13913",title:"Dr.",name:"Umashankar",surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5166",title:"Echocardiography in Heart Failure and Cardiac Electrophysiology",subtitle:null,isOpenForSubmission:!1,hash:"cb992fb172cb9aa79234394e1704ecc2",slug:"echocardiography-in-heart-failure-and-cardiac-electrophysiology",bookSignature:"Umashankar Lakshmanadoss",coverURL:"https://cdn.intechopen.com/books/images_new/5166.jpg",editedByType:"Edited by",editors:[{id:"13913",title:"Dr.",name:"Umashankar",surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6536",title:"Cardiac Arrhythmias",subtitle:null,isOpenForSubmission:!1,hash:"60225e652fdad9957fb2bad71795510f",slug:"cardiac-arrhythmias",bookSignature:"Umashankar Lakshmanadoss",coverURL:"https://cdn.intechopen.com/books/images_new/6536.jpg",editedByType:"Edited by",editors:[{id:"13913",title:"Dr.",name:"Umashankar",surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7907",title:"Practical Applications of Electrocardiogram",subtitle:null,isOpenForSubmission:!1,hash:"e6ccea0e539a40209a7d3c8507108832",slug:"practical-applications-of-electrocardiogram",bookSignature:"Umashankar Lakshmanadoss",coverURL:"https://cdn.intechopen.com/books/images_new/7907.jpg",editedByType:"Edited by",editors:[{id:"13913",title:"Dr.",name:"Umashankar",surname:"Lakshmanadoss",slug:"umashankar-lakshmanadoss",fullName:"Umashankar Lakshmanadoss"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6209",title:"Endothelial Dysfunction",subtitle:"Old Concepts and New Challenges",isOpenForSubmission:!1,hash:"f6e76bbf7858977527679a6e6ad6a173",slug:"endothelial-dysfunction-old-concepts-and-new-challenges",bookSignature:"Helena Lenasi",coverURL:"https://cdn.intechopen.com/books/images_new/6209.jpg",editedByType:"Edited by",editors:[{id:"68746",title:"Dr.",name:"Helena",surname:"Lenasi",slug:"helena-lenasi",fullName:"Helena Lenasi"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6373",title:"Myocardial Infarction",subtitle:null,isOpenForSubmission:!1,hash:"10bca0bf18d68ec3c1641dbc3a1ae899",slug:"myocardial-infarction",bookSignature:"Burak Pamukçu",coverURL:"https://cdn.intechopen.com/books/images_new/6373.jpg",editedByType:"Edited by",editors:[{id:"70686",title:"Dr.",name:"Burak",surname:"Pamukçu",slug:"burak-pamukcu",fullName:"Burak Pamukçu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7556",title:"Dyslipidemia",subtitle:null,isOpenForSubmission:!1,hash:"dfd1faefe925f0f8335c42cdb36256c1",slug:"dyslipidemia",bookSignature:"Samy I. 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Duraibabu",slug:"dinesh-babu-duraibabu",email:"dineshbabu.duraibabu@ul.ie",position:null,institution:{name:"University of Limerick",institutionURL:null,country:{name:"Ireland"}}},{id:"269578",title:"Dr.",name:"Gabriel",middleName:null,surname:"Leen",fullName:"Gabriel Leen",slug:"gabriel-leen",email:"Gabriel.Leen@ul.ie",position:null,institution:{name:"University of Limerick",institutionURL:null,country:{name:"Ireland"}}},{id:"269579",title:"M.Sc.",name:"Fintan",middleName:null,surname:"McGuinness",fullName:"Fintan McGuinness",slug:"fintan-mcguinness",email:"Fintan.McGuinness@ul.ie",position:null,institution:{name:"University of Limerick",institutionURL:null,country:{name:"Ireland"}}},{id:"269580",title:"Dr.",name:"Gerard",middleName:null,surname:"Dooly",fullName:"Gerard Dooly",slug:"gerard-dooly",email:"Gerard.Dooly@ul.ie",position:null,institution:{name:"University of Limerick",institutionURL:null,country:{name:"Ireland"}}}]},book:{id:"8271",title:"Applications of Optical Fibers for 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It is a multimodal and biopsychosocial event with an individual objective and subjective occurrences, resulting in significantly diverse perceptions of pain between the individuals. One of the most common reasons for a patient to visit an endodontist is dental pain. Managing dental pain and anxiety during and after treatment is still a difficult task, which depends on the clinician’s skill and knowledge [2].
In symptomatic pulp tissue diagnosed with irreversible pulpitis, extracellular levels of Substance P are elevated. When comparing pulp tissue diagnosed with irreversible pulpitis to clinically normal pulp tissue, an 8-fold rise in Substance P was found [3]. As a result, irreversible pulpitis is linked to high peptidergic system activation. It is generally known that root canal preparation causes inflammation in the periapical tissues, explaining why root canal therapy causes post-treatment pain (such as symptomatic apical periodontitis). SP is released in the periodontal ligaments as a result of varied canal preparation approaches, which was found to be quite interesting. However, the amount of released SP differs among procedures. Inflammation in the periapical tissues could be triggered by an elevation in SP [4]. This might thus be considered a key mediator of neurogenic inflammation and related hyperalgesia, and hence a prospective target for therapeutics targeted at regulating pain and minimizing the harmful effects of tissue injury [5].
When a carious lesion gets close to the pulp, the pulp’s inflammatory alterations get worse. An acute exacerbation of chronic inflammation occurs at this stage, with an influx of neutrophils and the release of inflammatory mediators (prostaglandins and interleukins), proinflammatory neuropeptides and mediators (substance P, Bradykinin, and calcitonin gene related peptide) [6]. These mediators can increase pain perception and neuronal excitability by stimulating peripheral nociceptors within the pulp of the affected tooth. This causes moderate-to-severe discomfort. Conventional procedures may not provide sufficient anesthesia. As a result, endodontists must achieve profound anesthesia in order to alleviate the pain [7].
The use of local anesthetic agents in pain management plays a vital role. It is the safest and most effective medications to prevent and manage pain during dental treatment [8]. Today’s availability of a variety of local anesthetic agents allows dentists to choose an anesthetic with specific properties such as time of onset and duration, hemostatic control, and degree of cardiac side effects that are suited for each individual patient and dental operation [9]. 2 percent lignocaine (Xylotox, Adcock Ingram; Xylesthesin, 3 M) with 1:80000 adrenaline content, 3 percent mepivacaine (Carbocaine) without a vasoconstrictor and 4 percent articaine (Ubistesin 3 M) with either 1:100000 or 1:200000 adrenaline concentration is currently the most commonly used local anesthetic agents in general dentistry [10]. Each local anesthetic has its own maximum recommended dose (MDR) measured in mg/kg body weight. Unfortunately, the literature7 shows that the mg/kg MDR for each drug ranges from 4.4 mg/kg 8 to 6.6 mg/kg [11, 12].
When dealing with a tooth that has been diagnosed with irreversible pulpitis or “Hot” tooth, it’s critical to determine whether enough local anesthetic has been attained. Subjective and objective testing has historically been used to validate successive inferior alveolar nerve block (IANB). Signs such as lip numbness, probing the gingiva surrounding the tooth to be treated, and so forth are examples of subjective tests [13]. Patients should not suffer discomfort throughout therapy if they respond favorably to the subjective results. These approaches, however, are not confirmatory test for detecting pulpal anesthesia.
While it’s possible that the operator’s inability to deposit anesthetic solution close to the targeted nerve would result in an insufficient blockade in both normal and non-inflamed states, it’s also possible that a partial blockade would suffice in neurons that inflammatory mediators did not sensitize. It’s crucial to understand the nerve supply to the anesthetized tissue and the anatomy of the injection site and any changes [14].
During a local infiltration at the root apex, however, the cortical bone of the body of the mandible can effectively block the anesthetic. The maxillary cortical bone is often thinner. Anesthetic diffusion is more easily achieved through this bone. Therefore, infiltration anesthesia, which is routinely used in the maxilla, would be less affected by anatomic variance. Block anesthesia is advised in the mandible because it is more predictable. Still, it demands a deeper awareness of the deep anatomy of the jaw and is more technique sensitive, which is why anesthetic failures in the mandible are more common. Inadequate local anesthetic has also been linked to accessory innervation of the mandibular teeth from various sources. The nerve to the mylohyoid muscle, in particular, has been linked to the transport of afferent fibers from the mandibular teeth [14]. The clinician has many alternatives for overcoming accessory innervations from the mylohyoid nerve, including using a blocking technique that deposits anesthetic solution higher in the pterygomandibular space.
The pH of the anesthetic solution determines the ratio of RN to RNH+. According to the Henderson–Hasselbalch equation, there are equal amounts of half-charged and half-uncharged molecules when the acid dissociation constant Pka equals the pH of the solution. In a cartridge of local anesthetic solution, both charged (RNH+) and uncharged (RN) molecules exist in equilibrium. The deionized lipid-soluble (RH) form penetrates the neuronal membrane and takes up H+. RNH+ within the nerve, resulting in RNH+, which enters the sodium channel and blocks conduction. To produce anesthesia, the body buffers the pH-injected anesthetic solution to the physiological pH [15].
This becomes potentially critical since inflammation-induced tissue acidosis can cause local anesthetics to get “ion trapped.” According to this theory, the low tissue pH causes a higher proportion of the local anesthetic to be held in the charged acid form of the molecule, preventing it from passing through cell membranes. This theory has been proposed as a primary cause of local anesthetic failures in situations like endodontic pain [16].
Local anesthetic failures may be exacerbated by central sensitization. Increased sensitivity may enhance incoming sensory nerve impulses. There is a significant response to peripheral stimuli in central sensitization, and as a result, the IANB may allow adequate signaling to occur, leading to the experience of pain [16].
According to this hypothesis, the nerves on the exterior of the nerve bundle supply the molar teeth, while the nerves on the inside supply the anterior teeth. Even if the anesthetic solution is placed in the right location, it may not disperse enough into the nerve trunk to reach all nerves and cause a sufficient block. This concept may only apply to the increased failure rates associated with IANB in the anterior teeth, not the posterior teeth [17].
The Tetrodoxin resistant channels (TTXr) family of sodium channels have been demonstrated to be resistant to the effects of local anesthesia. Anesthetic failures in a hot tooth are caused by increased expression of sodium channels in the pulp. The TTXr channels are resistant to lidocaine, resulting in insufficient anesthetic [18]. TTXr channels are expressed on nociceptors, and their activation with Prostaglandin E2 is relatively resistant to lidocaine. Because they are less susceptible to lidocaine, sodium channels that are resistant to TTX. As the concentration of lidocaine rises, the sodium channels get blocked [19].
Inflamed tissue nerves have a lower excitability threshold and an altered resting potential. Lower excitability thresholds are responsible for impulse transmission [20].
Anxiety in the patient may also play a role in the local anesthetic failure. Clinicians who have worked with anxious patients know that they have a lower pain threshold and are more likely to complain about an unpleasant dental experience. The sight of a needle and the sound of the dental handpiece are frequently reported as causes of anxiety in patients. Furthermore, patients may be particularly apprehensive about root canal therapy.
Inflammation has several additional consequences on the physiology of local tissues. Inflammatory mediators cause peripheral vasodilation, which increases the rate of systemic absorption, lowering the concentration of local anesthetics. Local anesthetics, in most circumstances, need formulation with vasoconstrictor drugs. Thus, this is a potentially relevant mechanism. Although regional variations in blood flow occur in inflamed dental pulp, little is known regarding inflammation-induced vascular alterations in periradicular tissue [21]. Furthermore, this vasodilation is likely to be confined and not seen at distant injection sites. As a result, compared to nerve block anesthesia, this concept may be more useful in understanding issues with infiltration anesthesia.
Inflammation alters the production of many proteins in nociceptors, resulting in a rise in neuropeptides such substance P and calcitonin gene-related peptide. These neuropeptides have an essential role to perform have a role in regulating pulpal inflammation. Furthermore, tissue damage can change the composition, distribution, and activity of sodium channels expressed on the nociceptors. Inflammation’s effect on these sodium channels might substantially impact local anesthetic failures [22].
Tachyphylaxis is a condition in which a receptor agonist medication causes a reduction in responsiveness to a subsequent dose of the drug. Because local anesthetics are frequently used in conjunction with vasoconstrictors, the medication may remain in the tissue long enough to trigger tachyphylaxis at the sodium channel. This has been suggested as a factor in decreased anesthetic efficacy, particularly after many administrations [21].
Contrary to popular belief, most moderate-duration anesthetics are equally efficient in inducing deep pulpal anesthetic for root canal treatment. Understanding the anatomical, local, and psychological aspects of each patient against the type of anesthetic utilized is critical to success. Most dentists prefer to employ a combination of anesthetics and a vasoconstrictor. When some types of anesthetic drugs are used, it is possible that the patients would experience more pain. Because of the acidic nature of local anesthetics, lower pH values are considered to produce a burning sensation during injection [23].
The injection location might influence injection discomfort. According to one study, maxillary buccal injections with plain 2% lidocaine Was found to be considerably less discomfort than 2% lidocaine with 1:80000 epinephrine. However, using the same anesthetic drugs, no difference in injection discomfort was recorded at the palatal location [12]. The type of anesthetic solution has little effect on injection discomfort when a location with less connective tissue (such as the palatal site in the maxilla) is injected. Faster injection speed leads to increased drug distribution. It has been proposed that a speed of injection exposes a larger portion of a nerve to the anesthetic solution, resulting in a higher rate of local anesthesia success. The rapid injections, on the other hand, produced more pain and discomfort during the procedure [23, 24, 25].
In individuals with symptomatic irreversible pulpitis, the degree of preoperative pain might impact anesthetic success. The activation of nociceptors during inflammation might be one reason for the lower success rate of inflamed pulp. The peripheral and central pain pathways are altered and modulated by the barrage of painful stimuli, as well as tissue destruction. Another reason for failure is that nerves from inflamed tissue have reduced excitability thresholds and altered resting potentials [26].
Inflamed pulps may have more tetrodotoxin-resistant sodium channels, which are resistant to local anesthetics. Prostaglandins, which can influence tetrodotoxin-resistant receptors and reduce nerve responses to anesthetic drugs, have also risen considerably in inflamed pulps [27]. As a result, premedication with nonsteroidal anti-inflammatory medicines (NSAIDs) and corticosteroids to increase anesthetic success appear to be a viable option. However, the findings of such research do not agree on the effectiveness of premedication on anesthetic success [28, 29]. However, if the patient does not have spontaneous pain, pre-treatment with particular types of NSAIDs may improve the effectiveness of anesthesia when treating irreversible pulpitis [30]. Premedication with corticosteroids before anesthesia with an inferior alveolar nerve block (IANB) injection resulted in a considerably better success rate.
Genetics may play a role in predisposing specific individuals to problems such as discomfort, delayed healing, and abscess development. A range of genetic variations influences pain perception and behavior. Pain becomes significantly more common in women, and various explanations have been proposed, including hormonal and genetically driven sex variations in brain neurochemistry [27].
Intraligamentary anesthesia is a technique wherein local anesthetic solution administered via the periodontal ligament to reach the pulpal nerve supply. The use of conventional or customized syringes can be used for this technique. At the mesiobuccal aspect, the needle is placed as deeply between the root surface and alveolar bone at a 30° angle to the long axis of the tooth. The needle can be placed with the bevel pointing in either direction, and 0.2 ml of the solution should be injected per root using back pressure. For 5 to 10 seconds, the needle is held in place [31]. The anesthetic action begins almost immediately and lasts for around 15–20 minutes [32].
In comparison to other anesthetic techniques, Intraligamentary anesthesia allows for a substantial reduction in the overall volume of anesthetic solution and vasoconstrictor supplement. At the same time, the unintentional intravascular application is avoided [33]. Furthermore, the effectiveness of Intraligamentary anesthesia is limited in cases of severe marginal periodontitis or teeth with a sclerotic periodontal gap, and alternate anesthetic methods such as inferior alveolar nerve block can be advised [32].
Intraosseous Anesthesia is more invasive and necessitates the use of specialist equipment, such as a perforator (e.g., Stabident, X-Tip). The gingiva must first be sedated for the perforator to penetrate without discomfort. A slow-speed handpiece is used to move the perforator into the anesthetic gingiva and bone until the cancellous bone is felt like a sharp dip. The perforator is then withdrawn, and a small 27-gauge needle is introduced through the perforation, injecting approximately 1 mL of solution over 2 minutes. It’s one of the most effective supplemental methods available [34]. The intraosseous injection permits the local anesthetic solution to be injected directly into the cancellous bone adjacent to the tooth that has to be sedated [35]. The intraosseous anesthetic onset of anesthesia is immediate and lasts for around 15 to 30 minutes, and was found to be more efficient than intraligamentary anesthesia [36].
After a failed IANB, buccal infiltration has been utilized as a supplemental anesthetic for anesthetizing mandibular molar teeth, especially in symptomatic irreversible pulpitis. A mandibular buccal infiltration injection of 4% articaine with 1:100,000 epinephrine as an additional injection to improve the effectiveness of the IANB injection has recently been investigated. The usage of the articaine solution was shown to be better than the lidocaine solution in asymptomatic individuals (88 percent vs. 71 percent, respectively) [37]. Only 58% anesthesia was achievable with buccal infiltration injection when used as a supplement to the IANB in case of symptomatic irreversible pulpitis [38].
Intrapulpal anesthesia is one of the supplementary anesthesia that is beneficial, especially in a hot tooth. The most crucial aspect of this technique is to pump the fluid into the pulp forcefully. If the physician does not feel pressure or resistance to injection, the solution is not reaching the pulp and is most likely running out of the pulp chamber and back into the access cavity [39]. However, this type of anesthesia is excruciating and should only be used as the last option during endodontic therapy. Intrapulpal anesthesia has the drawback of having a limited duration of effect. As a result, it’s critical to remove the pulp from all of the root canals as soon as possible after injection to avoid repeated injection [40]. It is necessary that the patient should be informed that the type of anesthesia will cause moderate to severe discomfort in the beginning.
Buffered local anesthesia technique to one of the techniques to improve the efficiency of the local anesthetics. Alkalinization accelerates the dissociation of the LA molecule, increasing in the uncharged base form that penetrates the nerve membrane and acts in the intraneuronal location. The addition of sodium bicarbonate is the most frequent technique for buffering LAs. The addition of sodium bicarbonate to local anesthetics reacts to form sodium chloride water and carbon dioxide. Alkalinization with sodium bicarbonate raise the pH of the solution. Carbon dioxide produces an independent anesthetic effect by changing the local anesthetic inside the nerve direct depressant effect of carbon dioxide on the nerve axon [41]. 50 mEq is the maximum dose of sodium bicarbonate. 20 ml of 1 or 2% lignocaine is recommended to be added with 2 ml of 8.4 percent sodium bicarbonate. The ratio of lignocaine to bicarbonate should be between 5:1 and 10:1 for best effects. If the bicarbonate level exceeds this ratio, precipitation may occur. In individuals with metabolic acidosis and hypocalcemia, this method is contraindicated [15].
Pain being the most common symptom, every effort should be made to manage it during and after root canal treatment and should be informed priorly the type of anesthesia administered to the patient. Although various anesthetic agents and techniques are available, the choice of them is specific and customized to each patient and their preoperative status and clinical condition. So, ultimately, the clinician should critically decide on a specific agent or a technique for the clinical condition of the patient. It is necessary to provide appropriate pulpal anesthesia when treating teeth with irreversible pulpitis.
The authors declare no conflict of interest.
As the world population is projected to grow close to 10 billion by 2050, we need to produce about 50% more food compared to 2013 production to meet the global demand [1]. This goal needs to be met while facing the challenges of climate change, the limited scope of arable land expansion, and dwindling water resources. In addition, anticipated food production also needs to incorporate practices for sustainable management of croplands to preserve soil health, conserve water resources, and encompass biodiversity [2]. Considering these challenges and constraints in achieving our food production targets there is an unprecedented need for monitoring of crop growth and health and timely interventions to maintain or improve crop productivity while reducing wastage of inputs and resources. Advances in sensors, communication technologies, computational systems, and powerful data analytics are enabling us to accomplish these tasks. Technologies that can enable efficient use of agricultural inputs and reduce environmental losses while contributing to increased and sustainable production are of great value for achieving food security. Several existing and emerging tools and technologies such as geographic information system (GIS), remote sensing (RS), Global Positioning System (GPS), Artificial Intelligence (AI), Big Data Analytics, and Internet of Things (IoT) are instrumental in achieving this goal through efficient monitoring of crops and soils, and, combined with other pieces of information, are providing data-driven insights for targeted or site-specific management of crops ensuring increased productivity [3]. Geographic Information System (GIS), a key foundational technology, is defined as a powerful system comprising tools for the collection, storage, and retrieval of data at will, as well as analyzing, transforming, and displaying the spatial data for a specific purpose [4, 5, 6, 7]. It plays a critical role as it provides the spatial context and information on several features each of which is available as a data layer. In addition, it provides the tools to manipulate spatial and non-spatial data and presents them through intuitive and illustrative map formats [8]. GIS has been making an impact in diverse domains that include geography, environmental sciences, natural resources, forestry, agriculture, food, manufacturing, banking, and health services [8]. Recent decades have seen a significant increase in the application of GIS tools for diverse applications in agriculture at local, regional, national, or global scales. These applications most often involve the use of GIS along with partner technologies such as remote sensing, GPS, and data analytics towards an in-depth understanding of a given farm or a region and facilitating intervention or corrective measures for the crops and/or the soils. Since the GIS data are linked to a common referencing system, another advantage GIS offers is that the same data can be used for different applications or goals and we can also bring in other data and, combining that with existing data, we can perform a joint analysis for deriving novel insights. Many studies have reported the use of GIS for diverse applications in different crops [9, 10, 11]. To further enable the readers to develop a strong appreciation for the role of this powerful technology in agriculture, here we have reviewed the most widely used and emerging applications of GIS, either by itself or in combination with other partner technologies, and how it has been making major impacts on agricultural productivity and supply chains.
\nThe power and impactful contributions of GIS in diverse domains can be attributed to the combined use of GIS and two other key geospatial technologies: GPS and Remote Sensing. Each of these three partner technologies plays a crucial role in realizing the goals of applications (Section 3), and, therefore, are briefly described below.
\nBased on its role in supporting the collection, storage, retrieval, and analysis of data on features and location, and its utility for data-driven solutions, especially in site-specific management, GIS is considered the brain of Precision Agriculture [12]. Digital GIS maps differ from conventional maps in that they harbor several layers of information each layer providing information or a map about a given attribute such as soil survey, precipitation, nutrient status, pest infestation, yield, etc. In addition, GIS provides the analytical capability by using statistical tools and geospatial analytics enabling extraction of inter-relationships between attributes, and the insights, thus derived, are valuable for decision making with respect to management practices.
\nThis positioning/navigation system based on a satellite network enables the determination of positional information by providing the latitude, longitude, and elevation of a location. The location information collected by GPS receivers enables farmers and researchers to the reliable identification of fields, mapping of field boundaries, water bodies, infested or problematic areas in the field, and for understanding the relation to several other attributes within and outside the boundaries of a given field. Such a high-fidelity field mapping permits site-specific application of nutrients, pesticides, herbicides, and water, thereby improving productivity and reducing input costs—the essence of precision agriculture.
\nRemote sensing, with its diverse methods and applications in agriculture, has revolutionized crop monitoring and interventions for improving farm productivity [13, 14]. RS, in combination with GPS, GIS, and other tools is critical for implementing the goals of precision agriculture. This combination is crucial for enabling several applications that provide the basis for site-specific management of fields and include soil mapping, crop growth monitoring, estimation of soil moisture and fertility, detection of biotic (pests and diseases) and abiotic (drought and flood) stresses, and yield estimation.
\nThe onset of digital agriculture, considered the fourth revolution in agriculture, has totally transformed the way farming is done, thanks to advances in geospatial technologies, sensors, artificial intelligence, robotics, and other tools and technologies. The ability to precisely identify the problem areas in cropland and monitoring and management of all steps in the entire agriculture value chain requires image and non-image data along with spatial context. GIS, with its component tools and analytic modules, and the data gathered by its partner technologies like remote sensing and GPS provides intuitive and lucid visualization of information for data-driven decision making for improving crop productivity. While GIS has been used for agricultural applications for quite some time, the number of applications has been growing rapidly in recent years due to technological advances. Several most common and emerging applications are presented and discussed below.
\nWe are in an era where we are facing the challenge of feeding billions of people while the fertile land is shrinking, therefore, we need to optimize the use of natural resources to maximize the benefits. GIS provides an excellent platform for assessing the quality of land for suitable applications. Multi-criteria decision-making (MCDM) approach based on GIS is the most popular choice among researchers for land use planning. Researchers use different features offered by GIS such as soil type distribution, soil texture map, buried deep underground water level distribution, soil fertility distribution, soil pollution distribution, hydraulic conductivity of soil (Ks), slope (S), soil texture (ST), depth to water-table (DTW), and electrical conductivity of groundwater (ECw), climate conditions, topography, and satellite data, and identify the variety of interactions, dependencies, and the impact of these interacting factors on sustainable land use.
\nChen et al. [15] evaluated weight sensitivity of MCDM model for land suitability assessment for irrigated agriculture. They aimed to examine the sensitivity of changing weights of the input features on the model output. The results suggested a strong influence of sensitivity and, therefore, they have recommended giving special emphasis on this criterion. Zolekar and Bhagat [16] have used GIS-based MCDM model with IRS P6 LISS-IV images as input for the evaluation of agricultural practices in hilly regions. The rank of influential criteria was determined by correlation analysis and recommendations from scientific literature. The combined use of remote sensing and GIS turned out to be beneficial for land suitability evaluation. Pan and Pan [17] applied three scales, two-step analytic hierarchy processes (AHP) for GIS-based crop suitability assessment. They have emphasized the importance of selecting appropriate evaluation factors and suggested the consideration of features with a significant difference and controlling the land use and avoiding causality. Following this approach of feature selection, the AHP output was spatially distinct. The authors have recommended appropriate land use based on land suitability maps. In another study, [18] selected the features based on growth requirements for examining the land suitability for the wheat crop. Analytic Network Process (ANP) model was deployed for assessing the interdependence of strategic input features for site suitability evaluation of citrus crops [19]. The ANP coupled with GIS–MCDM identified critical factors for maximizing yield and minimizing production loss. AHP integrated with geo-statistics had proven its merit for maize cultivation land suitability mapping in calcareous and saline-sodic soils [20]. These powerful GIS tools enable land reclamation planning with suitable conservation practices.
\nIntegrated fuzzy membership and GIS model were used to analyze arable land suitable for farming. Topography and eight soil parameters were utilized for fuzzy membership classification and the important crop productivity-related soil features were accommodated accordingly. Fuzzy membership allowed the consideration of partial memberships which is unlikely in classical approaches for classification. This self-adaptive approach revealed that the land was better suitable for groundnut cultivation contrary to the current practice of Finger millet cultivation. Results of this experiment proved that the GIS-based decision system can surpass the traditional knowledge and, if deployed accurately, can improve the productivity of land [21]. This is the need of the hour technology as land and natural resources are declining, and the demand for food production is increasing rapidly. The fuzzy set model, AHP, and GIS were combined to generate a land suitability map for tobacco production [22]. This study has once again demonstrated the advantage of using Fuzzy membership functions for land suitability analysis. AHP has the power of accurately assigning weights to the input factors in a logical way. The maps were generated by ArcMap. The integrated application of fuzzy, AHP, and GIS helped to circumvent the problems resulting from the uncertainties, subjectivities, and hierarchy characteristics of the traditional land suitability assessment process. GIS is a powerful tool to delineate the study area, manipulate geographic data, process maps, and present results in land suitability assessment. Integration of Fuzzy set and AHP methods with GIS provides a precise and powerful combination in applying for land suitability analysis. Researchers advocate that Fuzzy logic coupled with other decision-making methods is one of the best approaches for land suitability analysis [21, 22, 23]. Scientists are also exploring artificial intelligence along with GIS for efficient land use planning [23].
\nAbundance of water supply is a primary requirement for meeting the demand for food production by the ever-increasing global population. As indicated earlier, farmers have the responsibility of feeding about 10 billion people in 2050 which demands a 50% increment in food production compared to 2013 level [24, 25]. The availability of clean water is decreasing and dependence solely on rainfall is not a viable option for the farmers [26, 27]. In this challenging scenario, water resource management is the key to success. Irrigation is the best solution for meeting the water requirement in agriculture. GIS technology backed by remote sensing has already proved its merit for the management of water resources [28, 29, 30, 31]. Researchers strongly suggested that remote sensing can supplement the traditional geophysical models for groundwater potential assessment and recharge experiments [32, 33]. Many researchers supported the potential of GIS for groundwater management [34, 35]. Tripathi et al. [36] integrated the MODFLOW groundwater model with the GIS for watershed prioritization. Singh et al. [37, 38, 39] combined GIS and remote sensing for delineating groundwater potential zones. Lineament and hydro- geomorphological maps were prepared from remote sensing images. The delineated groundwater potential zones have been found to show synergy with the well-yield data. When sub-watershed level runoff and sediment yield were assessed using the combination of GIS and remote sensing data it reduced the time of the input data process and produced good results compared to actual runoff and sediment yield [40]. Determining the suitability of irrigation for a given geography is one of the most popular applications of GIS. A study conducted in UAE accounted for non-renewable sources like desalination and treated sewage effluent (TSE) to assess irrigation suitability [41]. This type of water-scarce region needs optimization of water resources management. Land management, topography, climate conditions, soil capabilities, and water potential were used in the analytical hierarchical process (AHP) GIS model to assess crop suitability. The results showed that the land was unsuitable for cereals and vegetables but the cultivation of sorghum, jojoba, fruits, date palm, and forage was recommended. This study unleashed the power of GIS technology for using every acre of fertile land in a geography with a high level of water scarcity. Reduction in clean water resources is motivating researchers and policymakers to identify suitable alternatives for irrigation water. [42] evaluated the scope of using urban treated wastewater as an alternate source of irrigation. They have utilized the MCDM method which was executed in the GIS software environment and the Analytic hierarchy process (AHP) was used. This analysis revealed that the suitability of treated wastewater is subject to suitability for crop cultivation, nitrate contamination burden, and aquifer vulnerability. ISAREG irrigation scheduling model was integrated with GIS with the aim of generating efficient irrigation scheduling advice and identification of practices to account for water savings and salinity control [43]. These results advocated the successful outcome of the model for irrigation scheduling and choosing water saving measures during both wet and dry years. Though the intensification of irrigation is beneficial for food production, it was pointed out that soil salinization and waterlogging are the major drawbacks of irrigated agriculture intensification, and that strong emphasis should be put on leveraging GIS and remote sensing technology for monitoring the problem areas followed by planning conservation and preventive measures [44].
\nSoil fertility is directly proportional to productivity. It controls the availability of nutrients and water to the crop. The soil fertility has been degrading due to various factors like pollution, sealing, overgrazing, waterlogging, excessive use of agricultural chemicals, and erosion. It is crucial to determine soil health and fertility status for planning effective practices for site-specific management or precision farming [45, 46, 47]. Soil macronutrients (N, P, and K), micronutrients (Zn, Mn, and Fe), pH, soil organic carbon (SOC), water holding capacity, erosion status, and moisture content are extensively used features for soil fertility status assessment [48, 49, 50, 51]. Spatial interpolation, Multi-Criteria Decision Analysis (MCDA) [52, 53, 54, 55], and Ordered Weighted Averaging (OWA) [56, 57, 58, 59] are the most popular geospatial analysis techniques which provide spatiotemporal variability of soil health and fertility status to the decision-makers.
\nSoil erosion status is an essential parameter for soil quality assessment and spatial variation in erosion gives a clear picture for agricultural planning [60]. It was demonstrated that geospatial maps of soil erodibility generated by Inverse Distance Weighted (IDW) method is a great tool for assisting in sub-watershed level land use planning. [61] combined the remote sensing and GIS technology to assess the soil fertility status. They have used the LISS III and IV images for land use classification and the RUSLE method for soil erosion estimation, collected the soil nutrient field data, and applied a geostatistical model to identify the spatial variation of soil erosion and nutrient availability. In another study, [62] used the IDW model for derived soil nutrient maps and applied the OWA method to make the maps homogenized and used those as the input for the fuzzy inference system for soil fertility mapping. Fuzzy mathematics developed with soil organic matter (SOC), total N, total P, total K, available N, available P, available K, pH value, and cation exchange capacity as indicators in ArcGIS showed that the soil fertility of mid- and low- yielding fields were low and are directly correlated with soil profile configuration [63]. The association of crop productivity with the soil fertility is evident and GIS-based soil maps and fertility status give prior information about the field-specific crop suitability.
\nLeena et al. [64] proposed GIS-enabled cloud technology for soil fertility management decision support system. This system has the capability to make fertilizer recommendation based on soil test and crop response. This recommendation system helps farmers optimize their fertilizer usage and maximize yield. This system generated spatial nutrient variation works as fantastic e-governance system for the government agencies. GPS- and GIS-based soil fertility maps are great tools for thorough monitoring of the soil health and, based on such maps, [65] recommended application of paper mill sludge to reduce acidity in the soil and cultivate pulses and groundnut to make the best use of the acidic soil. These geospatial soil maps have proven to be an effective decision support system in the context of food production challenges due to soil degradation. [66] applied soil fertility index (SFI) based on the variables of sand, silt, clay, pH, EC, OM, CaCO3, Ntotal, Pavb, Kexc, Caexc, Naexc, Mgexc, and available micronutrients (Feavb, Cuavb, Znavb, Mnavb) and proved the strength of SFI. This study demonstrated the potential of combining Sentinel 2 image-derived crop yield for validation of soil fertility model. Advances in the observatory systems such as remotely sensed data of fine-to-coarse spatiotemporal resolutions, and in the process-based and data-driven modeling techniques have facilitated the collection, storage, analysis, visualization, and interpretation of non-spatial data for soil fertility index (SFI) [67, 68, 69, 70, 71, 72].
\nLi et al. [72] applied weighted space fuzzy clustering coupled with the soil nutrient space mutation distribution for soil fertility characterization. This information aids in optimizing the fertilizer recommendation system. Agricultural practices such as crop residue management, nutrient management, soil tillage, and pest management affect ecosystem goods and services and soil quality and fertility [73, 74, 75]. The best management practices, compatible land use/cover changes, and land suitability analysis are required to prevent the degradation and loss of prime farmlands [73, 76, 77]. Soil erosion management, soil biodiversity improvement, and rehabilitative farming systems are some of the best management practices used to improve soil quality and crop yields [78, 79, 80].
\nA study that leveraged GIS and fuzzy evaluation method to evaluate the soil fertility status used total nitrogen, total phosphorus, total potassium, available nitrogen, available phosphorus, available potassium, soil organic matter, cation exchange capacity, and pH as indicators for the generation of fertility indices [63]. This fertility index revealed that total nitrogen and soil organic matter are higher for paddy fields. These fertility maps also give an insight into the suitable soil qualities under different types of land use and climatic conditions. Sub-watershed level nutrient mapping revealed that available N, P, S, Zn, and Fe are controlling agents of soil fertility [81]. Thus, fertility maps and their relationship with soil properties and crop yields serve as an information system for precision agriculture.
\nStudies have reported that biotic crop damage, caused by insects, fungi, and other pests, can cause 15–70% yield loss [82, 83, 84]. This scenario impacts the demand and supply chain and also affects the economy of farmers. The changing pattern of weather makes the crops susceptible to pests and diseases. The availability of crop protection methods is quite beneficial for tackling crop health, but the lack of timely information about the pests and diseases makes the damage irrepressible. GIS technology holds immense potential for site-specific pest and disease management. Remote sensing and GIS-based forewarning systems are boon to farmers to arrest the yield and economic loss. Ranjan and Vinayak [85] advocated that pest and disease forecasting systems allow farmers to apply the control measures in time to reduce the cost of production. Apart from the forewarning system, the pest population density map also plays a crucial role in identifying the hotspots and extending advisory to farmers. According to [86], information about the geospatial density of oriental fruit moth,
Natural calamities cause irreversible damage to agriculture. Rapid mapping and quantification of damage aid in economic loss recovery and act as a decision support system. A geo-spatial model is used in a case study to assess the impacts of extreme flood events on agricultural production in the Quang Nam province of Vietnam. [97] generated the water surface by interpolating flood depth marks by the inverse distance weighting (IDW) and employed a digital elevation model (DEM) to generate the flood inundation map. This map overlaid with the land use map gave an effective estimate of the damaged agricultural area [98, 99, 100]. Drought is another constraint to agricultural productivity and understanding the hotspot and climatology is crucial to strategically minimize the impact. MODIS satellite Normalized Difference Vegetation Index (NDVI) derived drought risk classes were prepared to access the spatial pattern [101]. GIS-based characterization of climate variability and drought zones provides scope for strategic measures adoption to maximize productivity [102, 103].
\nMonitoring of crop growth, health, and accurate or near accurate prediction of yield is crucial not only for estimating economic return but also for assessing the food production thereby helping in the management of food security. Many studies showed that traditional methods of crop yield estimation could lead to poor assessment and inaccurate crop area appraisal [104, 105]. Moreover, these methods require time-consuming, labor-intensive, and expensive crop and yield data collection. This is where technologies like remote sensing (RS), GPS, and GIS provide a huge advantage as they can be used to assess temporal and spatial variability of crop dynamics and yield output [106]. The use of two key partner technologies, RS and GIS, with required input from others can provide an efficient solution for monitoring crop health and developing models for predicting crop yields across diverse spatial scales. While remotely sensed images and associated analytics permit the tracking of crop health and predicting the yield, GIS technology enables the collection, storage, retrieval, and visualization of data that were linked geographically. Remotely sensed geospatial data acquired by satellites, aircrafts, or unmanned aerial vehicles (UAVs) can be used to gather information on several features of the crops and the characteristics of the soils supporting their growth thereby enabling the assessment of crop health. The images gathered can be used for assessing general vigor, disease or pest infestations, or deviations from expected growth due to drought or other abiotic stresses. Geospatial data collected in a spatiotemporal manner and the associated analysis techniques help in assessing the changes in the health of crops thereby permitting management interventions while providing predictions on anticipated yields based on the growth and health of the crops. A commonly used method for assessing crop health is based on the determination of vegetation indices that are calculated based on surface reflectance from crop canopies at two or more wavelengths. Many vegetation indices are available for evaluating the extent and vigor of vegetation, crop growth dynamics, stress due to biotic or abiotic factors, and other useful assessments [107]. Adhav et al. [108] used multiple vegetation indices that included Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Vegetation Index (CVI), and Difference Vegetation Index (DVI) to determine crop health as well as variations in health conditions. To further improve the efficiency of health assessment, they have combined all vegetation indices using ArcMap 10.5 software and reclassified the merged indices which were then used for categorical representation of health scenarios. Such a representation helps farmers to identify areas that need immediate management intervention [108]. Determination of crop health is particularly critical in smallholder farms as the subsistence and livelihood of these farmers depend on the productivity of their crops. As per a recent study, small farms were found to account for 84% of all farms worldwide but they operate only on around 12% of all agricultural land and produce about 35% of world’s food [109]. Use of UAVs for gathering and leveraging data for assessing crop growth and dynamics has proven to be crucial for farmers to take timely and appropriate corrective measures to maintain or increase productivity. A recent study in South Africa [110] evaluated the utility of multispectral UAV imagery and random forest machine learning (ML) algorithm to estimate maize chlorophyll content at various growth stages and created a chlorophyll variation map capturing the spatial heterogeneity of chlorophyll in the field thereby helping the farmers to take management actions. Considering the strategic role of sustainable intensification towards the food production goals of Sub-Saharan Africa [111], such RS- and GIS-based diagnostics and interventions are critical for smallholder farmers. Another study assessed crop health using different chlorophyll indices in addition to modified vegetation index by leveraging data from two different satellites and ArcMap (of ArcGIS) for geospatial analytics [112] resulting in insights that could be used for managing nutrient applications towards improving crop productivity. Two essential prerequisites to implement location-specific management practices and interventions are the availability of an accurate acreage map of crop of interest and the cropping systems of a given area and technologies for predicting yield before the reproductive phase or harvesting of the crop. The use of RS and GIS technologies can help achieve both goals. NDVI, a commonly used vegetation index, serves the dual purpose of assessing crop health and predicting crop yield while GIS tools can provide the spatial context. Several studies abound that leveraged NDVI and GIS for yield predictions and a few examples are discussed here. In a study that measured NDVI values at different growth stages of rice, several linear regression-based yield prediction models were developed using NDVI values and narrowed down to a model that had the highest prediction potential and was also able to predict yield well ahead of harvesting time [113]. Such a model can help the farmers to implement changes to the fertilization, water, pest, and disease management practices towards realizing improved productivity. Using time-series data of SPOT vegetation and two key spectro-agrometeorological variables, rainfall estimate (RFE) and NDVIactual (NDVIa), that are highly correlated to maize yield, [114] have developed an operational model with high predictive ability for yield forecasting in Ethiopia. By leveraging both RS and GIS, this model enabled yield forecast at flowering season which is more than two months earlier than the forecast by conventional method thus providing an advantage of early intervention towards crop productivity and crucial data for the authorities for crop production estimates [113]. In a field study aimed at developing an efficient model for predicting potato tuber yield using RS and GIS techniques two vegetation indices, NDVI and soil adjusted vegetation index (SAVI), generated from images acquired by Landsat-8 and Sentinel-2 satellites were found to be highly effective in yield prediction [115]. In addition, the indices enabled them to create maps of the study area that has clearly shown zones differing in productivity. This is very useful information for both farmers for implementing necessary management practices and for authorities in arriving at accurate production estimates. While manly researchers have used RS-based vegetation indices and GIS for predicting crop yields, several researchers have combined GIS with crop simulation or physiological models and demonstrated their strong performance in yield prediction [116, 117, 118, 119]. Crop simulation models came into prominence due to their utility in designing management practices, assessing the role of climate variations on crop performance, and predicting yields [120, 121]. Similarly, physiological crop models have evolved from their original applications in farm management to measuring the impact of climatic changes on crop productivity. The ability to incorporate spatial variability of the inputs that go into physiological or simulation models makes them even more powerful for determining the interactions between climatic variation and crop productivity while highlighting the spatial heterogeneity. In a study that integrated RS data, crop growth model, and GIS, it was found that yield estimates from RS images were more precise compared to another approach where GIS climate layers and soil attributes were integrated into Oryza 2000 rice crop model highlighting the superiority of combining RS, GIS, and crop model for estimating crop yields [118]. To capture the spatial variability of input variables and their influence on yield estimates, [116] have linked RS and GIS with a growth model of soybean. The results demonstrated spatial variability in simulated yield estimates and the variability was primarily attributed to soil characteristics and rainfall. The availability of such spatial patterns from the simulated yield estimates is very helpful in productivity estimates in areas prone to abiotic stresses, for example, droughts, as well as providing insights into factors contributing to yield. Efforts also exist that have created web-based decision support systems based on a combination of simulation model and GIS towards making agronomic decisions [119]. In yet another approach, the Erosion Productivity Impact Calculator (EPIC), a model for the analysis of the relationship between soil erosion and crop yield at field level, was integrated with GIS and an Inference Engine (IE) towards global estimation of crop productivity [122]. While the integration of GIS expands the application of EPIC to regional or global level, the availability of IE helps in determining potential crop combinations for given growing conditions. This study not only demonstrated the ability of GIS-based EPIC for crop productivity simulations at global level but also delivered predictions for future yields and how they are adversely affected by global climate change underscoring the importance of the development of climate-resilient varieties of crops. Since traditional crop productivity simulations are based on site-specific crop models, [123] developed an operational crop model that can be utilized at the regional level, North China, by integrating USDA EPIC model with NASA MODIS LAI product from Earth Resources Observation System (EROS), ancillary ground data, and GIS [123]. Applications also exist where a combination of GIS and RS was used for assessing damage in some high-value crops. Cranberry is one such crop that exhibits extreme crop yield variations due to soil characteristics which in turn influence water and nutrient availability. Using GIS, GPS, and RS, [124] have created a spatial variation map for the crop enabling the analysis of crop losses within zones in a field or at the whole field level.
\nPrecision Farming, also called Precision Agriculture (PA) or site-specific crop management (SSCM), is the application of technologies and principles to manage spatial and temporal variability associated with all aspects of agricultural production [125]. Earl et al. [126] defined it as a system that integrates information with crop production that is designed to increase long-term, site-specific as well as whole farm production efficiency, productivity, and profitability while minimizing unintended impacts on wildlife and the environment [126]. The operational goals of precision farming include better management of inputs such as seeds, fertilizers, pesticides, herbicides, and water using right amounts of inputs at the right place, and at the right time. Several crucial tools and systems such as GPS, GIS, and RS are required for the collection of timely geospatial information on soil-plant-animal requirements towards mining insights followed by leveraging those insights for prescribing and applying site-specific treatments towards improving agricultural productivity while contributing to sustainability and protecting the environment [127, 128, 129]. The role of different tools and technologies as well as the applications of precision farming are described in several review articles and references therein [9, 128, 130]. While GPS, GIS, and RS are vital for obtaining and analyzing the data for deriving insights, a key technology that implements the precision applications by leveraging the input of these three tools is variable rate technology (VRT). VRT systems take all the required information about a field such as soil maps, yield, infestation of pests, diseases, and weeds, and they determine the quantities of fertilizers, pesticides, herbicides, and other inputs and ensure their application at the right place and at the right time saving the input costs. The integration of GIS, GPS, and VRT technologies thus provides farmers an unprecedented ability to view field maps and apply input where and when needed towards ensuring crop productivity. Precision farming can be broadly divided into three steps or stages depending on data collection or site-directed or specific activities happening during, before, and after the crop growth period [131]. These are Preparatory or Pre-planting stage, Crop growth stage, and Harvesting stage. Role of GIS in each of these stages is discussed below.
\n\n
\n
\n
Renewable sources of energy are crucial to achieving climate change and sustainability goals. Agricultural residues are a promising source of biomass-based energy the demand for which is rapidly increasing around the globe. One challenge with agricultural residues for efficiently channeling them for energy production is the fact that their availability is seasonal and is geographically widely distributed. A solution that can address this spatio-temporal variability, seasonal fluctuations in biomass supply levels, and identification and transport of residues to power plants is a critical prerequisite for biomass-based energy generation. GIS, in combination with remote sensing, can be a great tool for precise identification and assessment of the crop residues and for planning a given region’s feedstock material for renewable energy and its economical transportation to power plants. GIS-based estimation of bioenergy potential enables a technologically advanced solution for leveraging the residues from existing cropping practices that promise even more benefits as the farmers shift from conventional to smart farming [139]. Some of the efforts in leveraging GIS and its partner technologies to this end are discussed below. Methods that can predict biomass potentials of a given region containing weather and crop production variations are of high value for enabling an efficient supply chain from biomass to power plants. By using BioSTAR, a carbon-based crop model, [140] have calculated biomass potentials for maize, triticale, and cup plant, and linked them with a GIS map of the soil dataset of Hannover region in Germany and demonstrated the utility of this method for predicting agricultural potentials under diverse environmental and crop management practices and conditions [140]. In a study that mapped rice cropland in a rural area in India, images from WorldView-2 satellite were used and the resulting map along with agricultural production statistics was analyzed in GIS for assessing the availability of rice straw as a feedstock for generating bioenergy [141]. In addition, the study also estimated the annual rice straw availability and the electrical power it could generate, thus providing valuable information for energy developers and policymakers for planning. Since the success and sustainability of a biomass-based energy generation project depend on several factors that include the feedstock resource, logistics, and environmental considerations, the role and value of GIS and key associated tools and technologies need to be understood prior to establishing the supply chain and the power plants. Two tools can help to address this task: GIS and life cycle assessment (LCA). While GIS is critical for assessing the resources dispersed in small or large areas, LCA is useful in evaluating the environmental impacts of bioenergy production projects. A comprehensive review on the application of LCA, especially spatial LCA, in understanding the impact of biomass-based energy generation on different ecosystem services and the value of integrating LCA and GIS to conduct a holistic assessment of environmental benefits in connection with bioenergy production recommended the inclusion of LCA as an essential component in planning bioenergy projects [142]. To assess the spatial and temporal availability of crop residues and to pinpoint locations for ideal power plants along with cost considerations, an integrated GIS-based biomass, site optimization, and logistics cost model was developed by using soil erosion, soil conditioning index (SCI), and crop residue yield indicators [143]. To estimate crop residues, prediction models based on artificial neural networks (ANNs) were developed for each of these indicators and were implemented on a GIS platform. The utility of this model was also demonstrated using a sustainable assessment of cotton stalks (CS) that are used to produce fuel pellets. An advantage of this model is that its use can be extended to assessment of multiple types of crop residues [143]. Models based on GIS and multi-criteria inclusion-exclusion analysis and facility location-allocation were also developed for the identification of sustainable crop biomass at larger spatial and longer temporal scales and to suggest ideal biogas plants along with cost considerations for biomass delivery [144].
\nGIS technology has proved to be of great value in understanding and optimizing agricultural supply chains and its use is being extended to diverse crops and locations. For ease of understanding its impact on supply chains can be discussed using the following three categories.
\nGIS technology has the potential to assist the successful transition of traditional agriculture systems to smart systems. While there are many studies that have thoroughly investigated the role of big data analytics in supply chains of diverse industries, such studies are lacking in the application of big GIS analytics (BGA) in agriculture. To this end, a systematic review of recent literature examined the role of BGA in agricultural applications and has proposed a framework for supply chains where BGA can play even a bigger role in improving the quality of GIS applications in agriculture [145]. The proposed framework serves as a useful reference for scientists and authorities for the successful management of big GIS data and leveraging it for improving productivity. The utility of Geographical Information Technologies (GITs) for improving the complex supply chain management process in the cotton crop was explored and was found to be of great value since the GITs framework enables visualization of current states as well as alternative options and what-if analyses for all steps that require decision making [146]. Another important application for which GIS was used is the analysis of supply chain patterns and description of spatial components of safe crop product (SCP) in China [147]. By using the spatial functions provided by GIS such as representation, location, analysis, traceability coding, and other techniques, tracing and retracing of the quality of safe crop product (SCP) was achieved. This system was also successfully demonstrated in a real supply chain for (re)tracing of SCP. By developing a GIS-based constrained linear programming model for minimizing transportation and storage costs for soybean and its byproducts, and further optimizing this model using General Algebraic Modeling System (GAMS), [148] have identified the lowest cost supply chains. The origin to destination cost matrices and geographic data maps required for the model development and optimization was developed by ArcGIS Network Analyst and ArcMap, respectively. This study demonstrated the combinatorial utility of ArcGIS, ArcMap, and GAMS for developing optimal supply chains that are of value to the players in the process [148].
\nProduction of biofuels from renewable sources such as agricultural residues can reduce the usage of fossil fuels thereby helping in the reduction of greenhouse gases. Identification of ideal locations for establishing biofuel facilities and designing a cost-effective supply chain for transferring biomass to the facility is highly desirable. To this end, in one approach a decision support system (DSS) has been developed by integrating a GIS-based method and two modeling methods, simulation, and optimization [149]. While GIS-based method was used for selecting facility sites, the selected sites were run through simulation and optimization modeling, and together these three methods provided an integrated DSS for assessing the cost, energy use, and emissions for the facility candidates as well as minimizing supply chain costs. In another approach, an intelligent spatial decision support system (ISDSS) was proposed to overcome the drawbacks of GIS in enabling creation of a knowledge base that supports decision making. The ISDSS combines GIS and intelligent systems and has spatial data mining capability through IoT devices [150].
\nThe sustainability of a biomass-based power plant depends on, among other things, a consistent supply of the feedstock, an economical supply chain, and an optimal location of the facility. The GIS-based analysis enables the identification of an ideal location for the plant and in making valid decisions related to the supply chain development. Using open-source GIS software, Latterini et al. [151], have simulated the identification of suitable locations for a small size power plant in Lazio region of Italy that can use olive prunings as the feedstock. This user-friendly and low-cost procedure, which can also be extended to other feedstocks, also provided supply chain costs for the evaluation of different sites and can serve as a useful tool for stakeholders in the development of economical biomass-based end-to-end supply chains [151]. In another study, an integrated approach combining GIS-based analysis with optimization modeling was developed resulting in a support system for decision-makers in comparing facility candidates and in minimizing supply chain costs [152]. The system developed could also be used for similar supply chains such as low capital biodiesel plants.
\nThe use of GIS in agriculture has increased at a rapid pace during the recent decades and the number of applications and the prominence of GIS has further amplified in the recent years due to advances in digital technologies that have been leveraging GIS as an essential partner technology for assessing crops, soils, and their environments. As discussed in this chapter, GIS is being used at all stages of agricultural value chain. In addition to the historical, current, and popular uses of GIS in land suitability/use planning and management of water, soil, and biotic and abiotic stresses, the advent of digital agricultural tools and technologies has increasingly leveraged the capabilities of GIS in new and emerging applications in high fidelity crop monitoring, yield prediction, precision farming, and supply chain management for both primary produce and biomass utilization towards energy production. The multitude of capabilities and insights provided by GIS, including the recent enhancements to collect and analyze data in real time, has further elevated its importance in providing location/spatial intelligence needed for improving the productivity and profitability of farms through precision practices. With the current and emerging applications, in combination with existing and newer partner technologies, GIS has a pivotal role in achieving sustainable agricultural productivity.
\nWe would like to thank Anu Swatantran for the support and helpful discussions, Chris Seifert, Andrea Arias, and Brian Lutz for support and funding, and Jochen Scheel, Steve Callistein, Janae Lehman Bell, and Nicole Janovick for rapid review and approval of the manuscript.
\nThe authors declare no conflict of interest.
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\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
\n\nA Conflict of Interest can be identified at different phases of the publishing process.
\n\nIntechOpen requires:
\n\nCONFLICT OF INTEREST - AUTHOR
\n\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
\n\nCONFLICT OF INTEREST – ACADEMIC EDITOR
\n\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
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\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
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On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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